{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Deep Autoencoder Networks\n",
    "\n",
    "High-dimensional data can be converted to low-dimensional codes by training a multilayer neural\n",
    "network with a small central layer to reconstruct high-dimensional input vectors.\n",
    "This kind of neural network is named *Autoencoder*.\n",
    "\n",
    "Autoencoders is *nonlinear dimensionality reduction* technique ([Hinton et al, 2006](https://www.cs.toronto.edu/~hinton/science.pdf)) used for unsupervised learning of features, and they can\n",
    " learn low-dimensional codes that work much\n",
    "better than principal components analysis as a tool to reduce the dimensionality of data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Anomaly Heart Beats Detection\n",
    "\n",
    "If enough training data\n",
    "resembling some underlying pattern is provided, we can train the network to learn the patterns in the data.\n",
    "An\n",
    "anomalous test point is a point that does not match the typical data patterns. The autoencoder will\n",
    "likely have a high error rate in reconstructing this data, indicating the anomaly.\n",
    "\n",
    "This framework is used to develop an anomaly detection demonstration using a\n",
    "deep autoencoder. The dataset is an ECG time series of heartbeats and the goal\n",
    "is to determine which heartbeats are outliers. The training data (20 “good”\n",
    "heartbeats) and the test data (training data with 3 “bad” heartbeats appended\n",
    "for simplicity) can be downloaded directly into the H2O cluster, as shown below.\n",
    "Each row represents a single heartbeat."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checking whether there is an H2O instance running at http://localhost:54321. connected.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td>H2O cluster uptime:</td>\n",
       "<td>1 hour 57 mins</td></tr>\n",
       "<tr><td>H2O cluster version:</td>\n",
       "<td>3.11.0.99999</td></tr>\n",
       "<tr><td>H2O cluster version age:</td>\n",
       "<td>9 hours and 4 minutes </td></tr>\n",
       "<tr><td>H2O cluster name:</td>\n",
       "<td>arno</td></tr>\n",
       "<tr><td>H2O cluster total nodes:</td>\n",
       "<td>1</td></tr>\n",
       "<tr><td>H2O cluster free memory:</td>\n",
       "<td>13.48 Gb</td></tr>\n",
       "<tr><td>H2O cluster total cores:</td>\n",
       "<td>12</td></tr>\n",
       "<tr><td>H2O cluster allowed cores:</td>\n",
       "<td>12</td></tr>\n",
       "<tr><td>H2O cluster status:</td>\n",
       "<td>locked, healthy</td></tr>\n",
       "<tr><td>H2O connection url:</td>\n",
       "<td>http://localhost:54321</td></tr>\n",
       "<tr><td>H2O connection proxy:</td>\n",
       "<td>None</td></tr>\n",
       "<tr><td>Python version:</td>\n",
       "<td>2.7.12 final</td></tr></table></div>"
      ],
      "text/plain": [
       "--------------------------  ----------------------\n",
       "H2O cluster uptime:         1 hour 57 mins\n",
       "H2O cluster version:        3.11.0.99999\n",
       "H2O cluster version age:    9 hours and 4 minutes\n",
       "H2O cluster name:           arno\n",
       "H2O cluster total nodes:    1\n",
       "H2O cluster free memory:    13.48 Gb\n",
       "H2O cluster total cores:    12\n",
       "H2O cluster allowed cores:  12\n",
       "H2O cluster status:         locked, healthy\n",
       "H2O connection url:         http://localhost:54321\n",
       "H2O connection proxy:\n",
       "Python version:             2.7.12 final\n",
       "--------------------------  ----------------------"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import h2o\n",
    "from h2o.estimators.deeplearning import H2OAutoEncoderEstimator\n",
    "h2o.init()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os.path\n",
    "PATH = os.path.expanduser(\"~/h2o-3/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parse progress: |█████████████████████████████████████████████████████████████████████████████| 100%\n",
      "Parse progress: |█████████████████████████████████████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "train_ecg = h2o.import_file(PATH + \"smalldata/anomaly/ecg_discord_train.csv\")\n",
    "test_ecg = h2o.import_file(PATH + \"smalldata/anomaly/ecg_discord_test.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "let's explore the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20, 210)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_ecg.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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4z+zZzBMm4Ppr1QKxEuFvcDD+FisG8hVSdsf27cwtW+K41q0hUKSl6e1//cV8zz0QYojQ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aAAAg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\nAhwRc0EQBEEIcP4/yprgvig65ogAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddab0a5710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# transpose the frame to have the time serie as a single colum to plot\n",
    "train_ecg.as_data_frame().T.plot(legend=False, title=\"ECG Train Data\", color='blue'); # don't display the legend"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "in the train data we have 20 time series each of 210 data points. Notice that all the lines are compact and follow a similar shape. Is important to remember that when training with autoencoders you want to use only VALID data. All the anomalies should be removed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's use the AutoEncoderEstimator to train our neural network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "deeplearning Model Build progress: |██████████████████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "model = H2OAutoEncoderEstimator( \n",
    "        activation=\"Tanh\", \n",
    "        hidden=[50], \n",
    "        l1=1e-5,\n",
    "        score_interval=0,\n",
    "        epochs=100\n",
    ")\n",
    "\n",
    "model.train(x=train_ecg.names, training_frame=train_ecg)             "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Details\n",
      "=============\n",
      "H2OAutoEncoderEstimator :  Deep Learning\n",
      "Model Key:  DeepLearning_model_python_1477202989522_3313\n",
      "Status of Neuron Layers: auto-encoder, gaussian distribution, Quadratic loss, 21,260 weights/biases, 274.4 KB, 2,000 training samples, mini-batch size 1\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>layer</b></td>\n",
       "<td><b>units</b></td>\n",
       "<td><b>type</b></td>\n",
       "<td><b>dropout</b></td>\n",
       "<td><b>l1</b></td>\n",
       "<td><b>l2</b></td>\n",
       "<td><b>mean_rate</b></td>\n",
       "<td><b>rate_rms</b></td>\n",
       "<td><b>momentum</b></td>\n",
       "<td><b>mean_weight</b></td>\n",
       "<td><b>weight_rms</b></td>\n",
       "<td><b>mean_bias</b></td>\n",
       "<td><b>bias_rms</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>210</td>\n",
       "<td>Input</td>\n",
       "<td>0.0</td>\n",
       "<td></td>\n",
       "<td></td>\n",
       "<td></td>\n",
       "<td></td>\n",
       "<td></td>\n",
       "<td></td>\n",
       "<td></td>\n",
       "<td></td>\n",
       "<td></td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>50</td>\n",
       "<td>Tanh</td>\n",
       "<td>0.0</td>\n",
       "<td>1e-05</td>\n",
       "<td>0.0</td>\n",
       "<td>0.0057908</td>\n",
       "<td>0.0025901</td>\n",
       "<td>0.0</td>\n",
       "<td>-0.0013594</td>\n",
       "<td>0.0915895</td>\n",
       "<td>0.0000773</td>\n",
       "<td>0.0310732</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>210</td>\n",
       "<td>Tanh</td>\n",
       "<td></td>\n",
       "<td>1e-05</td>\n",
       "<td>0.0</td>\n",
       "<td>0.0086898</td>\n",
       "<td>0.0034284</td>\n",
       "<td>0.0</td>\n",
       "<td>-0.0007684</td>\n",
       "<td>0.0904266</td>\n",
       "<td>-0.0012694</td>\n",
       "<td>0.0166782</td></tr></table></div>"
      ],
      "text/plain": [
       "    layer    units    type    dropout    l1     l2    mean_rate         rate_rms         momentum    mean_weight         weight_rms       mean_bias          bias_rms\n",
       "--  -------  -------  ------  ---------  -----  ----  ----------------  ---------------  ----------  ------------------  ---------------  -----------------  ---------------\n",
       "    1        210      Input   0.0\n",
       "    2        50       Tanh    0.0        1e-05  0.0   0.0057907675873   0.0025900984183  0.0         -0.00135939235415   0.0915895402431  7.7344572897e-05   0.0310732275248\n",
       "    3        210      Tanh               1e-05  0.0   0.00868983275151  0.003428385593   0.0         -0.000768360794937  0.0904265940189  -0.00126938133686  0.0166782140732"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "ModelMetricsAutoEncoder: deeplearning\n",
      "** Reported on train data. **\n",
      "\n",
      "MSE: 0.00247308999996\n",
      "RMSE: 0.0497301719277\n",
      "Scoring History: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>timestamp</b></td>\n",
       "<td><b>duration</b></td>\n",
       "<td><b>training_speed</b></td>\n",
       "<td><b>epochs</b></td>\n",
       "<td><b>iterations</b></td>\n",
       "<td><b>samples</b></td>\n",
       "<td><b>training_rmse</b></td>\n",
       "<td><b>training_mse</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.054 sec</td>\n",
       "<td>0.00000 obs/sec</td>\n",
       "<td>0.0</td>\n",
       "<td>0</td>\n",
       "<td>0.0</td>\n",
       "<td>0.3882908</td>\n",
       "<td>0.1507697</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.097 sec</td>\n",
       "<td>4545 obs/sec</td>\n",
       "<td>10.0</td>\n",
       "<td>1</td>\n",
       "<td>200.0</td>\n",
       "<td>0.1252225</td>\n",
       "<td>0.0156807</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.120 sec</td>\n",
       "<td>6153 obs/sec</td>\n",
       "<td>20.0</td>\n",
       "<td>2</td>\n",
       "<td>400.0</td>\n",
       "<td>0.0969532</td>\n",
       "<td>0.0093999</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.143 sec</td>\n",
       "<td>7058 obs/sec</td>\n",
       "<td>30.0</td>\n",
       "<td>3</td>\n",
       "<td>600.0</td>\n",
       "<td>0.0812936</td>\n",
       "<td>0.0066087</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.179 sec</td>\n",
       "<td>8264 obs/sec</td>\n",
       "<td>50.0</td>\n",
       "<td>5</td>\n",
       "<td>1000.0</td>\n",
       "<td>0.0609603</td>\n",
       "<td>0.0037162</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.197 sec</td>\n",
       "<td>8759 obs/sec</td>\n",
       "<td>60.0</td>\n",
       "<td>6</td>\n",
       "<td>1200.0</td>\n",
       "<td>0.0562246</td>\n",
       "<td>0.0031612</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.220 sec</td>\n",
       "<td>8805 obs/sec</td>\n",
       "<td>70.0</td>\n",
       "<td>7</td>\n",
       "<td>1400.0</td>\n",
       "<td>0.0525046</td>\n",
       "<td>0.0027567</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.236 sec</td>\n",
       "<td>9195 obs/sec</td>\n",
       "<td>80.0</td>\n",
       "<td>8</td>\n",
       "<td>1600.0</td>\n",
       "<td>0.0503764</td>\n",
       "<td>0.0025378</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.252 sec</td>\n",
       "<td>9523 obs/sec</td>\n",
       "<td>90.0</td>\n",
       "<td>9</td>\n",
       "<td>1800.0</td>\n",
       "<td>0.0497302</td>\n",
       "<td>0.0024731</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.269 sec</td>\n",
       "<td>9852 obs/sec</td>\n",
       "<td>100.0</td>\n",
       "<td>10</td>\n",
       "<td>2000.0</td>\n",
       "<td>0.0503726</td>\n",
       "<td>0.0025374</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2016-10-23 01:08:56</td>\n",
       "<td> 0.272 sec</td>\n",
       "<td>9756 obs/sec</td>\n",
       "<td>100.0</td>\n",
       "<td>10</td>\n",
       "<td>2000.0</td>\n",
       "<td>0.0497302</td>\n",
       "<td>0.0024731</td></tr></table></div>"
      ],
      "text/plain": [
       "    timestamp            duration    training_speed    epochs    iterations    samples    training_rmse    training_mse\n",
       "--  -------------------  ----------  ----------------  --------  ------------  ---------  ---------------  --------------\n",
       "    2016-10-23 01:08:56  0.054 sec   0.00000 obs/sec   0         0             0          0.388291         0.15077\n",
       "    2016-10-23 01:08:56  0.097 sec   4545 obs/sec      10        1             200        0.125223         0.0156807\n",
       "    2016-10-23 01:08:56  0.120 sec   6153 obs/sec      20        2             400        0.0969532        0.00939992\n",
       "    2016-10-23 01:08:56  0.143 sec   7058 obs/sec      30        3             600        0.0812936        0.00660866\n",
       "    2016-10-23 01:08:56  0.179 sec   8264 obs/sec      50        5             1000       0.0609603        0.00371615\n",
       "    2016-10-23 01:08:56  0.197 sec   8759 obs/sec      60        6             1200       0.0562246        0.0031612\n",
       "    2016-10-23 01:08:56  0.220 sec   8805 obs/sec      70        7             1400       0.0525046        0.00275673\n",
       "    2016-10-23 01:08:56  0.236 sec   9195 obs/sec      80        8             1600       0.0503764        0.00253778\n",
       "    2016-10-23 01:08:56  0.252 sec   9523 obs/sec      90        9             1800       0.0497302        0.00247309\n",
       "    2016-10-23 01:08:56  0.269 sec   9852 obs/sec      100       10            2000       0.0503726        0.0025374\n",
       "    2016-10-23 01:08:56  0.272 sec   9756 obs/sec      100       10            2000       0.0497302        0.00247309"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our Neural Network is now able to *Encode* the time series.\n",
    "\n",
    "Now we try to Compute reconstruction error with the Anomaly detection function.\n",
    "This is the Mean Square Error between output and input layers.\n",
    "Low error means that the neural network is able to encode the input well, and that means is a \"known\" case.\n",
    "A High error means that the neural network has not seen that example before and so is an anomaly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "reconstruction_error = model.anomaly(test_ecg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now the question is: Which of the test_ecg time series are most likely an anomaly? \n",
    "\n",
    "We can select the top N that have high error rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = reconstruction_error.as_data_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df['Rank'] = df['Reconstruction.MSE'].rank(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Reconstruction.MSE</th>\n",
       "      <th>Rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>9.780837</td>\n",
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       "      <th>22</th>\n",
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       "      <td>0.004101</td>\n",
       "      <td>5.0</td>\n",
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       "      <th>16</th>\n",
       "      <td>0.003689</td>\n",
       "      <td>6.0</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.003129</td>\n",
       "      <td>7.0</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.003078</td>\n",
       "      <td>8.0</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.003051</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.002889</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.002757</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.002545</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.002510</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.002386</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.002369</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.002261</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.002158</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.001957</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.001613</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.001565</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.001069</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.000813</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.000722</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Reconstruction.MSE  Rank\n",
       "21            9.780837   1.0\n",
       "22            7.441649   2.0\n",
       "20            2.931406   3.0\n",
       "14            0.004800   4.0\n",
       "4             0.004101   5.0\n",
       "16            0.003689   6.0\n",
       "15            0.003129   7.0\n",
       "18            0.003078   8.0\n",
       "12            0.003051   9.0\n",
       "6             0.002889  10.0\n",
       "17            0.002757  11.0\n",
       "9             0.002545  12.0\n",
       "1             0.002510  13.0\n",
       "2             0.002386  14.0\n",
       "5             0.002369  15.0\n",
       "3             0.002261  16.0\n",
       "0             0.002158  17.0\n",
       "11            0.001957  18.0\n",
       "19            0.001613  19.0\n",
       "10            0.001565  20.0\n",
       "7             0.001069  21.0\n",
       "13            0.000813  22.0\n",
       "8             0.000722  23.0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sorted = df.sort_values('Rank')\n",
    "df_sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Reconstruction.MSE</th>\n",
       "      <th>Rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>9.780837</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>7.441649</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2.931406</td>\n",
       "      <td>3.0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Reconstruction.MSE  Rank\n",
       "21            9.780837   1.0\n",
       "22            7.441649   2.0\n",
       "20            2.931406   3.0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anomalies = df_sorted[ df_sorted['Reconstruction.MSE'] > 1.0 ]\n",
    "anomalies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = test_ecg.as_data_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fdda69e5590>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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lg29+xw6MUzT8l1/WwYLFi8NNICbRb76BRh4To8+RyD2ZMyMdsUoVCConT7rf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\nS06GBjxsmPcLaAcxNwYFQTNv2hRmXblBt90GAhU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cJtHqs8rr+PdfCJ+euu9J4JunksHX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sUg\nw5wc5EazUuXt43DAYpCcDM3z008VySUk4G+vXoh2j4+HiZr9xnfeiTl97lwIH50748PafXIy0s+6\ndMHY5s61ju6/dAla+gsvSPm732EcQqg0NuMnPBwa77XXwuLxwgv4GCP0Gxqk/POfYQnOysI4kpPh\nMhAC14hz1z/7TAkg7j7jx0u5dWvLcVdUoHiP1Tbx8VBgv/MdpNLhGPbJXEiQrl8QQvQkomoimiSl\nXGPxey4RbSHaQkS5JASGTUQUGYmi8zExKLA/eTJRdTWa13fpgv7RP/85GgW46ymrodEWKC8nWrwY\nDR1OnybKzkajiJISLCsqQrMJIjRpuP129FM29knW0Ag0Dh4k+u53id57D806CgqI3nwTfbtjY9G0\nqrKS6MIFrO9woDlK795oMJKXhwYiUVFqn7t3E/3+90SHD2P9yEg0I8rNxTGGDyfq00fNwb17E2Vl\n4Xi1tXhPNm0ieustNFA5cADNVaKj8Xt2NrbbuVMtT0hA0xUpMdYDB4iuvx4NiZ56CssSEog2bCDq\n1cvetWlsxPXYuRPn8Otfo8HSvn1EP/oRxvHyy+g/bvc9XbmSaOpUovnzib79bXWcr3wF/cwXLULz\nm5oa1+3i49E8yR1v1dWhp3tTk1rW3Ix5Z/NmzDH79xOFhxNNmFBEhYV5RER5UsoiT+NtLZmnENFu\nIhoppSyx+D2XiLb06LGFampyXX6LiSFKTsZkWVODi0SEmzxpEh5aYxN6DY1ggZSYJDp3xuSmoXEl\nsXQpuoIdP050zz1E115LVFoKYk5NBWnn5IAgVq0COfDnxImW+4uJIUpMRFeymho80w4H0bFj6vfu\n3SEYdO0KompqIlqwAITdpw/It7ER44iIAJE1NoJEH3qI6KtfJdq6lei114j+8Q+i+nrse8AAnENK\nCtZ94QWsk5KCjoPDhuF927ABY58xA2RtxqFDRPPmoSOn00mUlARhZPRo/D93Ls4vNha88sADECCM\nxN7URFRWho5sb78Nwh0zhmjNGqx39CjO5ZNP0BntxhsDfGMNqKnBeKqqiigvr43JXAghiOhDIoqT\nUk52s04uEW3ZsmULJSfnUmEhJLjjx/Gpr4cEmJeHz/DhuIlaE9fQ0NBwDzbOOnxoYi0llKfmZtfl\n3buDrJxOaKP//jeIf+dOoosXsV1MDLarqwNZR0ZCmD15EsvDw0FuDzwA4UIItFr905+gwY4YQfTc\nc9Di33gDVlgprVu5Pvoo0T//SVRVBUI+dYqouBi/9e5NdOutRHFxav3aWuwzPp7oj38k6t+f6NVX\ncQ7btuEY119PNHQoCHLZMuyvd2+QdVwcSLy4WLVI7t8fFoi0NJxbeTmEi6gotDy94QZf7pb/KCq6\nMmT+MhHNIKLxUkrLTqxM5pMmTaIuXbq4/DZnzhyaM2eOX8fW0NDQ0LiykBI9uF95BcSXlaUUscxM\nmNCtUFRE9M1vYtsuXaAljxiB33r1wva9eoF4q6rQs72piej999G7PT4eQkJCAkh6yRJXgUQICBLP\nPIN1jTh9Glr2G28oYveGLl1aWty6dye66y6iO++EdaItsGDBAlqwYIHLsrNnz9KqVauI2orMhRAv\nEtGXiWiilPKgh/W+0Mxzc3PdraahoaGh0YHhdILU09Nh6m4P1NURbd+ufNxduyIWZscOCA9hYTDr\nJyUFj3XYF8083NedXybym4hosici19DQ0NDQIII7YNSo9h1DbCzR2LEtl/fte+XH0hbwicyFEH8g\nojlENIuILggh+lz+6ayUsiHQg9PQ0NDQ0NDwDh/CJ4iI6EEiiieiQiI6YvjcHthhaWhoaGhoaNiF\nT5q5lNJX8tfQ0NDQ0NBoY2hy1tDQ0NDQCHFoMtfQ0NDQ0AhxaDLX0NDQ0NAIcWgy19DQ0NDQCHFo\nMtfQ0NDQ0AhxaDLX0NDQ0NAIcWgy19DQ0NDQCHFoMtfQ0NDQ0AhxaDLX0NDQ0NAIcWgy19DQ0NDQ\nCHFoMtfQ0NDQ0AhxaDLX0NDQ0NAIcWgy19DQ0NDQCHFoMtfQ0NDQ0AhxaDLX0NDQ0NAIcWgy19DQ\n0NDQCHFoMtfQ0NDQ0AhxaDLX0NDQ0NAIcWgy19DQ0NDQCHFoMtfQ0NDQ0AhxaDLX0NDQ0NAIcWgy\n19DQ0NDQCHFoMtfQ0NDQ0AhxaDLX0NDQ0NAIcWgy19DQ0NDQCHFoMtfQ0NDQ0AhxaDLX0NDQ0NAI\ncWgy19DQ0NDQCHFoMtfQ0NDQ0AhxaDLX0NDQ0NAIcWgy19DQ0NDQCHFoMtfQ0NDQ0AhxaDLX8IgF\nCxa09xA0/IS+d6ELfe9CF+1173wmcyHERCHEIiFElRDCKYSY1RYD0wgO6EkldKHvXehC37vQRciQ\nORF1IqJtRPQNIpKBHY6GhoaGhoaGrwj3dQMp5WIiWkxEJIQQAR+RhoaGhoaGhk/QPnMNDQ0NDY0Q\nh8+auY+IJiIqLS1t48NotBXOnj1LRUVF7T0MDT+g713oQt+70EUg752BO6O9rSuk9N/tLYRwEtHN\nUspFbn7/KhG94/cBNDQ0NDQ0NO6UUv7N0wptrZkvIaI7iWg/ETW08bE0NDQ0NDQ6EqKJKInApR7R\nppq5hoaGhoaGRtvDZ81cCNGJiFKIiCPZBwshsojolJTyUCAHp6GhoaGhoeEdPmvmQojJRLSCWuaY\nvyml/O9ADUxDQ0NDQ0PDHlplZtfQ0NDQ0NBof+g8cw0NDQ0NjRCHJnMNDQ0NDY0QR8DIXAjRRwjx\neyFEpRCiQQhx4HJDlmsu/z5PCLFCCHH2coOW+EAdW8M32LhXhZfvEX+ahRB/MO3jSSHE50KIC0KI\nU+1zJh0bgXinhBDdhBDvXF7ntBDiL5eDWI3rPC+E2Hz5GLpSSYAQoPu33+Jd/L5pHX3/AgxP9+7y\nO/V7IUSZEKLu8m/Pm+/flX73ApJnLoQYRERriegUEX2XiHYRUQQRzSSiF4konYhiieiTy5+fBeK4\nGr7D5r2SRPQnInqaVNZCnWlXEUT0LhGtIyId+BhgBPCd+hsR9SGiaUQUSURvENErRDTXsI4koleJ\nqICIMgN7JlcnAnj/JBH9kIj+TOpdPG+xjr5/AYKNe3cbESUQ0XeIqJSIBhHeqUQiut2wqyv77kkp\nW/0hoo+J6CARRVv8Fm/6PpmIms3L9efKfOzcK0K2wm9t7u8eQlpiu59bR/oE4p0iomFE5CSiHMOy\nGUTUREQJFvt9hoiK2vvcO8InUHMiEe0jokdsHlPfvyt87wzLbyOieiJyXP5+xd+9VpvZhRDdLg/y\nRSlliypvUspzrT2GRmDg4726UwhxQgixUwjxf0KImCs20KscAXynxhLRaSnlVsOypQRtoKDVA9Ww\nRBvMif8jhDgphCgSQjwuhAgLyEA1WqAV964rEZ2TUjovf7/i714gzOxcQGZ3APal0bawe6/eIaID\nRHSEYPr5JRGlEqRPjbZHoN6pBCKqNi6QUjZfjnFIaOW+NdwjkHPi80RURDD5jiOinxPu3eMB2LdG\nS/h874QQPQmukFcMi6/4uxcIMtc9zUMHtu6VlPIvhq/FQoijRLRMCJEspdzXNkPTMEC/U6GNgN0/\nKeXvDF93CSEaiegVIcQTUspLgTqOxhfw6d4JIeKI6COCX/3HbTIimwhENPsegulgWAD2pdG28Pde\nbSQ85CkBH5GGFQL1Th0jot7GBZdNtN0v/6bRNmjLOXEjQQlLaoN9a/hw74QQnQkNUM4Q0S1SymbD\nz1f83Ws1mUspTxNO6JtWflUhRJfWHkMjMGjFvcohPOBH23B4GpcRwHdqHRF1FULkGJZNIwhmG1o9\nUA1LtPGcmEMIrKr2tqKG77B77y5r5J8Sgt5mSSkbTate8XcvUHnm3ySiMCLaKIS4RQiRIoQYJoR4\nhBDiz3l7WUQ0lHBCmUKIrMsBBxpXDh7vlRAiWQjxQyFErhBikBBiFhG9SUQrpZS7eCdCiAGX7+cg\nIgq7fC+zzHmUGn6j1e+UlLKMMDH9WQiRL4QYT0S/J6IFUsovtAMhxBAhRDYhtSbGcC/bukVyR0ar\n758QYowQ4ttCiMzL7+WdRPRbIvqrlPIsH0jfv4DD2xwZR0SfEVIL7yeQdp/LHwdRO717AQzn70NE\nLxDRXoK0cpCI/kNEMwyh905CCobxc3d7pyJcbR9P94qI+hNRIRGdIOSW7ybkwHY27eN1i3vZTEST\n2vv8OsonEO8UIcr2bSI6S0SnCfnKsabjrHBzLwe29zUI5U9r7x9BC19HCH67QPDLfp+IIvT9a797\nRyqV0Phxmq/5lX73dKMVDQ0NDQ2NEIeuza6hoaGhoRHi0GSuoaGhoaER4tBkrqGhoaGhEeLQZK6h\noaGhoRHi0GSuoaGhoaER4tBkrqGhoaGhEeLQZK6hoaGhoRHi0GSuoaGhoaER4tBkrqGhoaGhEeLQ\nZK6hoaGhoRHi0GSuoaGhoaER4vh/CChcJni/uKAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdda87af950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.T.plot(legend=False, title=\"ECG Test Data\", color='blue')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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yGzYwXHoUtZhfA8ABoFEA27YHIJ8Mm5wr23TLFpGrr+bZb7iB8erHHqO4hoTk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\nJkE+xWXPZz4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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdda687cbd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = data.T.plot(legend=False, color='blue')\n",
    "data.T[anomalies.index].plot(legend=False, title=\"ECG Anomalies in the Data\", color='red', ax=ax);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions\n",
    "\n",
    "In this tutorial you learned how to use the autoencoding capabilities of H2O to quickly detect time series anomalies using Autoencoders."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unsupervised Pre-training with Supervised Fine-Tuning\n",
    "\n",
    "Sometimes, there is much more unlabeled data than labeled data.\n",
    "It this case,\n",
    "it might make sense to train an autoencoder model on the unlabeled data and\n",
    "then fine-tune the learned model with the available labels.\n",
    "\n",
    "[TODO](https://github.com/h2oai/h2o-3/blob/master/h2o-r/tests/testdir_algos/deeplearning/runit_deeplearning_stacked_autoencoder_large.R)\n",
    "[https://github.com/h2oai/h2o-3/blob/master/h2o-py/tests/testdir_algos/deeplearning/pyunit_autoencoderDeepLearning_large.py](https://github.com/h2oai/h2o-3/blob/master/h2o-py/tests/testdir_algos/deeplearning/pyunit_autoencoderDeepLearning_large.py)"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
